advertising analytics and bjp 2014

That historical 2014 Indian

Election BJP’s win..

What was the real secret behind this

achievement?

BJP = 282/543

282

What it just the effective

speeches that made BJP win?

Or the rallies and “MODI LEHER”…..??

It was a lot more….

Effective target

Advertising played

a key role in this

win…

But how did BJP targeted people so effectively in a country like India with huge diversity?

How did they analysed how much resources

they need to allocate to different areas and

segments of advertising?

The insight in HBR article

could provide the answers to our questions.. By Wes Nichols

What is meant by

It is the art of evaluating advertising effectiveness and performance.

ADVERTISING ANALYTICS

It quantifies impressions, clicks, conversions and buying behaviour that different ads generate.

ADVERTISING ANALYTICS

What are the of this article?

OBJECTIVES

What are the

of allocating resources in different areas of advertising ?

Traditional ways

It helped marketers link scanner data

with advertising and decide how to allocate

marketing resources.

Traditional ways

Marketers started tracking consumers most recent online action- say

a click on a banner ad and attributed a purchases

behaviour to it

Traditional ways

Different teams and marketers measure the performance of each of

their marketing activities as if they work independently

of one another

What are the

of using such traditional methods ?

The traditional ad techniques ignores the assisted effects of marketing.

Disadvantages

The change in an advertisement viewing behaviour due to influence of another ad of the same company.

Suppose, a user might see a T.V. ad & newspaper ad inspired and search Google , sees it banner later, click and make purchase.

Disadvantages Here, T.V. , newspaper, google search all have assisted in buying behaviour which these traditional methods could ignore and measure their effects independently.

Disadvantages

This could result in

over attribution or

under attribution of

advertising

revenues

What is the other big problem marketers could

face?

Virtually infinite record of data

LACK OF CAPABILITY OF STORAGE

LACK OF CAPABILITY

OF ANALYSIS

How should the company know that how ads assist

each other and which combination is the best?

What should be the right amount to be invested at

right points in the customer-decision journey?

The companies need to prepare segment of people by proper

analysis and then targeting them by al locating appropriate

resources.

are involved

3. ALLOCATION

1. ATTRIBUTION 2. OPTIMISATION

Analytics 2.0

It is the process of quantifying the

contribution of each element of advertising using analytics engine

storing huge data.

Analytics 2.0 - ATTRIBUTION

market

conditions

consumer

response

competitive

activities, marketing

actions

business

outcomes.

Data is collected across categories.. Analytics 2.0 - ATTRIBUTION

The huge data is stored using

and

where, record of every activities and their inter-related

effects could be analysed to allocate the marketing resources.

Analytics 2.0 - ATTRIBUTION

It runs various testing analytic tools to run scenarios for

business planning on a small scale.

Switching the shade of blue used on advertising links

in Gmail and Google search earned the company an

extra $200m a year in revenue.

Analytics 2.0 - OPTIMISATION

In a war-gaming process , team members define marketing

goals and software generates a set market scenarios and

recommendation to achieve them.

Elasticity points are given in respect that by how much percentage sales in changes by changing

any factor.

Analytics 2.0 - OPTIMISATION

Uses such test to place its ads to see, which has the maximum response.

uses an A/B framework (used to test the success of web marketing campaigns), allows multiple versions of the site to be live simultaneously. This helps the company conduct live experiments by siphoning off a small portion of traffic and studying the results

It redistributes the resources across

marketing activities according to

optimisation scenarios.

Analytics 2.0 – ALLOCATION

The Obama team in 2008 U.S. elections looked at 24 different

variations of the splash page using a mix of images and CTA buttons to determine which combination

produced the greatest results. Each variation was seen by more than

13,000 people

The winning combination saw a 40% increase in sign-up rates and

an additional 2.8 million email addresses which ultimately led to

$60 million in donations.

are involved

3. ALLOCATION

1. ATTRIBUTION 2. OPTIMISATION

One-of the world’s largest software gaming companies Successfully Attributed, Optimized, and Allocated to increase its selling and profit by increasing its revenue by 23% in a very popular game “BATTLE FIELD”

Analytics 2.0 allowed Samsung Mobile to

cost-effectively determine which markets

would shift the overall brand preference

score in their favor and the right

advertising techniques to target people.

What are the

1. Embrace analytics as an organization 2. Appoint an analytical minded person to tasks. 3. Conduct an inventory of data through

organization 4.Build limited scope models that aim to achieve

early wins 5. Aggressive testing and feeding of results.

- Traditional methods of advertising - Disadvantages - Move to analytics 2.0 - Attribution, optimisation, allocation - Ways of implementation

- Analytics can be used to find out the appropriate resources needed to allocate.

- The revenue of the company could take a high growth by applying analytics.

- Marketing is rapidly becoming a war of knowledge, insight, and asymmetric advantage gained through analytics 2.0 .

- Companies that don’t adopt next-generation analytics will be overtaken by those that do.

Coming back to the BJP case…

India consisted of :

-543 parliamentary and 4120 assembly constitution -930,000 polling booths

-Voter rolls in PDF’s in 12 languages

-900,000 PFD’s - Diverse range of voter names and information

Many companies like SAP, Oracle, InMobi, Modak Analytics were tasked with analysing data for electoral

campaign and developing customised tools for the elections.

A large professional data analytics team was appointed to process and filter data from various sources like

debates on mygov.in, social network, economic conditions of people etc.

The companies developed their own

customised digital tools based on

commisioned and open source data

including a 64 node Hadoop, PostgreSQL,

a d ser ers that process a aster file containing over 8 Terabytes of data.

Machine learning algorithms were

also developed to help categorize

people based on name, geography,

religion, caste and ethnicity.

They analysed historic voter pattern and newly available voter rolls to identify the pocket boroughs of their party, the booths unlikely to elect them and the ones that could go either way, or the swing booths.

It helped them know were to allocate resources and how much.

They even planted cookies in computers of people who visited their website to track their activities online and target them at the appropriate time.

Such twitter analysis

were also made to see

what are people

response.

BJP was able to categorise people on the basis of gender, age, race, religion and

interests through the digital tools.

Also, by proper analysis, the party segmented people on the basis of who are

likely to vote.

The party did ’t spe d o ey i those areas ore here the people ere sure of not voting BJP for any reason.

The party effectively targeted people at various places of their interest

The party was able to interact with people ith ariety of its progra s like Chai pe Charcha .

- HBR Article : Advertising Analytics 2.0

- http://dataconomy.com/narendra-modi-first-prime-minister-use-big-

data-analytics/

- http://articles.economictimes.indiatimes.com/2013-11-

26/news/44487290_1_data-analytics-bjp-and-congress-delhi-

bungalow

- http://www.cnbc.com/id/101571567

- http://www.firstpost.com/india/big-data-analysis-how-it-firms-like-

sap-oracle-helped-modi-win-1576355.html

- https://en.wikipedia.org/wiki/Big_data

Created by-

Deepali jain

HBTI, KANPUR

during an internship by Prof.

Sameer Mathur, IIM

Lucknow www.iiminternship.com